1. Field of the Invention
The present invention relates to prediction and diagnostic techniques for life span of a rotary machine used in a manufacturing apparatus. In particular, it relates to a diagnosis method for predicting the life span of a rotary machine such as a dry pump and a manufacturing apparatus including the rotary machine.
2. Description of the Related Art
In recent years, semiconductor manufacturing apparatus failure diagnostic techniques have become important to ensure efficient semiconductor device manufacturing. Especially as the trend towards many item/small volume production of system LSI grows, an efficient yet highly adaptable semiconductor device manufacturing method has become necessary.
There are methods of using a plurality of small-scale production lines to accomplish efficient semiconductor device production. However, if a large-scale production line is merely shortened, the capacity utilization of the manufacturing apparatus drops. Moreover, this causes the problem where investment efficiency falls. To rectify this situation, there is a method by which a plurality of manufacturing processes is performed with one piece of semiconductor manufacturing apparatus. In the case of low pressure chemical vapor deposition (LPCVD) apparatus using a dry pump for the evacuation system, reactive gases and reaction products differ and formation situations for the reaction products within the dry pump differ depending on the type of manufacturing processes. Therefore, the manufacturing process affects the life span of the dry pump. If the dry pump should have a shutdown during a specific manufacturing process, then the lot being processed becomes defective. Moreover, the excessive maintenance of the manufacturing apparatus may become necessary due to microscopic dust caused by residual reactive gases within the manufacturing apparatus. Implementation of such excessive maintenance causes the manufacturing efficiency of the semiconductor device to drop dramatically. If regular maintenance is scheduled with a margin of safety in order to prevent such sudden shutdowns during the manufacturing process, the frequency of maintenance work on the dry pump may become astronomical. Not only does this increase maintenance costs, but also the decrease in capacity utilization of the semiconductor manufacturing apparatus becomes remarkable due to changing the dry pump, causing the manufacturing efficiency of the semiconductor device to sharply decrease.
Previously, some methods of diagnosing dry pump life span have been proposed. Basically, a state of the dry pump may be monitored by characteristics such as the motor current, vibration, and temperature, and methods have been provided to predict life span from changes in these characteristics. In particular, dry pump life span diagnosis methods have mainly been provided monitoring the state of the dry pump through vibrations caused by the rotation of a rotor. Since a diagnosis using the vibration can be accomplished through measurements taken by merely attaching an accelerometer to a side of the dry pump, and it has gained attention as a simple and easy method for predicting life span. In addition, as a method for predicting life span through measured vibration data, there has been proposed a method where deviation from a reference value for a high frequency component near 300 Hz is analyzed using neural networks (refer to Japanese Patent Application P2000-64964).
In the case of the technology disclosed in Japanese Patent Application P2000-64964, since a targeted frequency is high, changes accompanying pump operation, such as reaction product blockage may broaden leading to a problem of decreased sensitivity.
Meanwhile, in order to use of semiconductor manufacturing apparatus in common for a plurality of processes, as is necessary for an efficient small-scale production line, it is desirable to accurately diagnose a vacuum pump life span and to operate the dry pump without having any waste in terms of time. Therefore, highly accurate life span prediction is essential. However, when an accelerometer is attached to the dry pump, sensitivity changes depending on where and how it is attached, and a collection of highly sensitive and stable vibration data is difficult.